Measuring Science Teachers’ Generative AI Literacy for Classroom Assessment: Performance Assessment

Ruiping Huang, Yue Yin


Abstract
We report preliminary analyses from an ongoing study using performance-based tasks to assess science teachers’ generative AI (GenAI) literacy for classroom assessment and compare these scores with self-reported GenAI use and confidence. Preliminary findings indicate moderate correlation with use frequency but weak correlation with confidence, highlighting performance assessments’ value.
Anthology ID:
2026.aimecon-wip.56
Volume:
Proceedings of the Artificial Intelligence in Measurement and Education Conference (AIME-Con): Works in Progress
Month:
October
Year:
2026
Address:
Wyndham Grand Pittsburgh Downtown, Pittsburgh, Pennsylvania, United States
Editors:
Joshua Wilson, Christopher Ormerod, Magdalen Beiting-Parrish
Venue:
AIME-Con
SIG:
Publisher:
National Council on Measurement in Education (NCME)
Note:
Pages:
448–458
Language:
URL:
https://aclanthology.org/2026.aimecon-wip.56/
DOI:
Bibkey:
Cite (ACL):
Ruiping Huang and Yue Yin. 2026. Measuring Science Teachers’ Generative AI Literacy for Classroom Assessment: Performance Assessment. In Proceedings of the Artificial Intelligence in Measurement and Education Conference (AIME-Con): Works in Progress, pages 448–458, Wyndham Grand Pittsburgh Downtown, Pittsburgh, Pennsylvania, United States. National Council on Measurement in Education (NCME).
Cite (Informal):
Measuring Science Teachers’ Generative AI Literacy for Classroom Assessment: Performance Assessment (Huang & Yin, AIME-Con 2026)
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PDF:
https://aclanthology.org/2026.aimecon-wip.56.pdf